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Comment by scribu | Hacker News Reader

Reading the examples, where people jumped on a single mistake to discredit an entire report points to some sad conclusions:

1. Scientific literacy is super low in the general population.

2. Motivated reasoning is rampant. People will believe anything that enables them to do what they wanted to do anyway.

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> 2. Motivated reasoning is rampant.

This is an important point. Scientific scrutiny is extremely important, but there is still a difference between a judge that is stern but fair - and one that actively wants you to fail.

Motivated reasoners have no problems holding opposing parties to impossibly high standards while accepting claims without any evidence as valid arguments for their side.

Today, climate scientists have learned the lessons and improved communication and modeling considerably, even to the point where we now how "attribution science" we we can discuss climate change in the context of particular weather events. We also start seeing changes in weather patterns that are hard to ignore even for laymen.

Nevertheless we are still having the same discussions as before.

> We also start seeing changes in weather patterns that are hard to ignore even for laymen.

Hard to ignore by motivated reasoners! Changes in weather patterns observed by individuals using their own experience are not evidence of global climate change. If there's science showing that, then yes, but personal experience doesn't add any value to the conclusion, it just reinforces whatever the person already wants to believe.

I think the author oversimplifies the problems with climate models. They've had numerous mistakes and extremely critical ones. Not least of which is that they haven't factored for Multi-decadal changes in cloud cover albedo. The climate system is incredibly complex and our models do not have good models for all the subsystems that make it up, including the oceanic oscillations like Atlantic Multi-decadal Oscillation, PDO, etc. We can't even predict many of these subsystems with any degree of accuracy so we are hopelessly inaccurate at the higher level.

I agree, and there are the same politician leanings in climate change non-profits and think tanks as with anything else. Sometimes they may justify sightly more alarming views of data to gain more funding; justifying it with, "Well, it's going to be bad anyway"

> We can't even predict many of these subsystems with any degree of accuracy so we are hopelessly inaccurate at the higher level.

Or do we? This sounds like a Fermi problem

https://en.wikipedia.org/wiki/Fermi_problem#Explanation

I may be wrong, though.

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